Signal Processing Engineer

TIMEZYX; Göteborgs kommun; Hybrid; SEK 550,000 - 750,000; Full time

Job summary

TIMEZYX in Gothenburg, Sweden seeks a Research Associate in SAR Signal Processing, Analytics & Modelling to join our Engineering team. The role focuses on fundamental SAR signal processing and algorithm development for extracting structural information from satellite SAR data.

You will develop and validate algorithms for InSAR, PS analysis, motion estimation, and displacement measurements, coordinating with Gothenburg and Vancouver colleagues and contributing to publications and R&D projects.

Qualifications

• PhD in Electrical Engineering, Signal Processing, Remote Sensing, Radar Engineering, Physics, Geomatics, Computer Science, or a closely related field
• Deep theoretical and practical expertise in SAR fundamentals, radar signal processing, and SAR image formation
• Demonstrated experience in developing and implementing SAR processing algorithms, beyond the application of standard software packages
• Strong knowledge of interferometric and coherent SAR processing, including phase analysis, displacement estimation, and time-series methods
• Strong scientific programming skills in Python, MATLAB, C/C++, or similar computational environments
• Strong analytical, research, and technical writing skills, with the ability to independently investigate open-ended research problems

Responsibilities

• Develop and implement advanced SAR signal processing and image formation algorithms, including phase-history, sub-aperture, backprojection, and autofocus methods
• Develop and validate InSAR and Persistent Scatterer (PS) analysis methods, including PS selection, geolocation, and association with physical locations on structures
• Develop methods for extracting dynamic structural response from SAR data using phase-based analysis, micro-Doppler, pixel tracking, etc.
• Investigate and optimize key processing parameters, including sub-aperture configuration, overlap, spatial/temporal resolution, and other algorithmic hyperparameters
• Incorporate structural and physics-based priors into SAR displacement and motion-estimation algorithms
• Validate SAR-derived measurements against EGMS products, ground-based sensors, and other reference measurements, including accuracy and uncertainty assessment
• Develop robust, well-documented processing pipelines and contribute to technical reports, publications, and collaborative R&D projects

Skills

Python

MATLAB

C/C++

Signal Processing

SAR Fundamentals

Inverse Problems

Technical Writing

Education

PhD in Electrical Engineering / related field

Tools

SNAP

StaMPS

MintPy

ISCE

GAMMA

Job description

TIMEZYX is a deep-tech company, focused on advancing the frontiers of Structural Digital Twin and revolutionizing risk assessment for critical infrastructure. Our mission is to solve the most complex computational challenges in science and engineering using innovative mathematical models, high-performance computing, and cutting‑edge machine learning techniques. At the core of our work is the development of robust numerical solvers and next‑generation simulation tools with applications in solid mechanics, physics‑based modeling, and uncertainty quantification.

We are proud to foster an inclusive, multidisciplinary research environment that brings together experts from structural engineering, computational mathematics, physics, computer science, and material science. As we continue to expand, we are looking for brilliant minds to join our team and help shape the future of risk assessment for critical infrastructure.

You can learn more about us on our website.

Position Overview:

TIMEZYX is seeking a Research Associate in SAR Signal Processing, Analytics & Modelling to join our Engineering team in Gothenburg, Sweden. This is a full‑time, remote/hybrid/in‑person industrial role developing advanced methods for extracting static and dynamic structural information from satellite SAR data.

The role has a strong emphasis on fundamental SAR signal processing and algorithm development, spanning SAR image formation, interferometry, phase-history and sub‑aperture processing, motion estimation, autofocus, and Persistent Scatterer analysis.

The successful candidate will develop, implement, validate, and improve algorithms for measuring structural displacement and dynamic response from SAR observations, including validation against ground‑based sensors and reference datasets, and will be working closely with colleagues across our Gothenburg and Vancouver offices.

The ideal candidate has deep theoretical and practical expertise in SAR fundamentals, strong scientific computing skills, and demonstrated experience developing SAR processing algorithms from first principles. Experience applying SAR methods to infrastructure monitoring, structural dynamics, or other precision deformation and motion‑estimation problems is highly desirable.

Key Responsibilities:

• Develop and implement advanced SAR signal processing and image formation algorithms, including phase-history, sub‑aperture, backprojection, and autofocus methods
• Develop and validate InSAR and Persistent Scatterer (PS) analysis methods, including PS selection, geolocation, and association with physical locations on structures
• Develop methods for extracting dynamic structural response from SAR data using phase‑based analysis, micro‑Doppler, pixel tracking, etc.
• Investigate and optimize key processing parameters, including sub‑aperture configuration, overlap, spatial/temporal resolution, and other algorithmic hyperparameters
• Incorporate structural and physics‑based priors into SAR displacement and motion‑estimation algorithms
• Validate SAR‑derived measurements against EGMS products, ground‑based sensors, and other reference measurements, including accuracy and uncertainty assessment
• Develop robust, well‑documented processing pipelines and contribute to technical reports, publications, and collaborative R&D projects

Qualifications:

• Ph.D. in Electrical Engineering, Signal Processing, Remote Sensing, Radar Engineering, Physics, Geomatics, Computer Science, or a closely related field
• Deep theoretical and practical expertise in SAR fundamentals, radar signal processing, and SAR image formation
• Demonstrated experience in developing and implementing SAR processing algorithms, beyond the application of standard software packages
• Strong knowledge of interferometric and coherent SAR processing, including phase analysis, displacement estimation, and time‑series methods
• Strong scientific programming skills in Python, MATLAB, C/C++, or similar computational environments
• Strong analytical, research, and technical writing skills, with the ability to independently investigate open‑ended research problems

Non-Technical Qualifications:

• Strong communication and technical writing skills
• Ability to work independently and lead research initiatives
• Strong problem‑solving and analytical thinking
• Adaptability in a fast‑evolving research and startup environment

Nice to Haves:

• Experience with InSAR, DInSAR, MT-InSAR, or Persistent Scatterer Interferometry
• Experience with raw, Level‑0, SLC, or phase‑history SAR data
• Experience with sub‑aperture processing, micro‑Doppler analysis, moving‑target analysis, or vibration estimation from radar
• Experience with SAR autofocus, including backprojection‑based or phase‑gradient autofocus methods
• Experience with pixel tracking, image registration, optical flow, or other motion‑estimation techniques
• Knowledge of structural dynamics, system identification, or structural health monitoring
• Experience incorporating physics‑based or structural priors into signal‑processing or inverse‑estimation methods
• Experience with SAR processing tools such as SNAP, StaMPS, MintPy, ISCE, or GAMMA
• Experience with high‑resolution SAR data from missions such as Sentinel‑1, TerraSAR‑X/TanDEM‑X, COSMO‑SkyMed, Capella, or other commercial SAR constellations
• Experience with machine learning, physics‑informed machine learning, inverse problems, or uncertainty quantification
• Prior work applying remote sensing or radar methods to bridges, buildings, or other infrastructure systems

Why Join TIMEZYX?

• Cutting‑Edge Research: Work on state‑of‑the‑art numerical and machine learning methods to solve real‑world scientific problems
• Collaborative Environment: Join a team of passionate, interdisciplinary researchers working across applied math, physics, and computing
• Professional Development: Opportunity to publish, present, and grow your research portfolio
• Inclusive Culture: A multicultural workplace committed to equity, diversity, and inclusion

Does this opportunity excite you?